Research On Tool Wear And Optimization Of Milling Parameters During Milling Of 42CrMo Die Stell

42CrMo die steel is a kind of high strength steel,which is widely used in mould manufacturing.As a difficult to process material,it has the disadvantages of serious tool wear and high milling temperature during the milling process,which greatly restricts its wide application.Therefore,it is of great significance to study the milling performance of 42 CrMo die steel and select the milling parameters reasonably,which is of great importance to improve the processing efficiency and reduce the production cost.In this paper,the influence of milling parameters on tool wear and milling temperature in milling process was studied by the method of combination of experiment and simulation.The main contents of this paper are as follows:The orthogonal test of tool wear was carried out.By measuring the wear of the ball end mill,the influence of the milling parameters on the tool wear was obtained.The empirical model of the wear increment and milling parameters was established by using the multiple linear regression method,and the accuracy of the model was verified by the test.Three sets of milling wear tests with variable milling speed were carried out on 42 CrMo die steel by using carbide ball end mill.The wear morphology of the tool surface was observed by means of SEM and EDS.The main wear mechanism types of the tool were analyzed.Based on the finite element software DEFORME-3D,the simulation model of die steel milling was established.The distribution of milling temperature in the milling process was studied.Through the orthogonal simulation test,the influence of milling parameters on the milling temperature was analyzed.Then,an empirical model of milling temperature was established by multiple linear regression method,and its significance was tested.The optimization model of milling parameters was established by milling the maximum tool life,maximum material removal rate and minimum milling temperature for milling 42 CrMo die steel.The optimal combination of milling parameters was obtained by using the genetic algorithm to solve the model.